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Background <p>Generative Artificial Intelligence (Gen AI) is a type of artificial intelligence that can learn from and mimic large amounts of data to create content such as text, images, music, videos, code, and more, based on inputs or prompts. Gen AI technologies are being increasingly integrated into healthcare education, including the field of nursing, where they are utilised to support a range of pedagogical activities.</p> Purpose <p>This scoping review examined and described the application of Gen AI as a teaching, learning and assessment strategy in Nursing education and examined the ethical implications of and attitudes towards its implementation.</p> Methods <p>We conducted a scoping review using a combination of methodological approaches, including Arksey and O’Malley’s 5-step framework, the PRISMA-ScR guidelines, and JBI evidence synthesis methods and searched five databases: EMBASE (Elsevier), Web of Science Core (Clarivate), CINAHL &amp; Medline (EBSCO), Applied Social Science Index and Abstracts, and ERIC (ProQuest). A wide search of grey literature was also conducted. Literature published in English between January 1st 2014, and July 1st 2025 was included in the review.</p> Results <p>Of the 1,251 articles retrieved, we identified 103 articles for inclusion in the review. There were 44 discussion/opinion/conference papers and 59 empirical research papers. Gen AI has predominantly been used for content creation simulation, personalised learning, tutoring, skill development and assessment. Students and Educators describe mixed attitudes towards the implementation of Gen AI, with several ethical concerns regarding the application of Gen AI in nursing education evident, including privacy, transparency, bias, and accountability issues.</p> Conclusion <p>While there is growing openness to Gen AI, a body of work remains regarding ethical and educational challenges. Recommendations for educational practice and curriculum development include a need for clear policies and guidelines to ensure the ethical use of Gen AI resources by educators and students. Further research is needed to understand long-term effects and promote responsible implementation within the context of nursing education.</p>

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Applications, attitudes and ethical considerations of Generative Artificial Intelligence (Gen AI) in nursing education: a scoping review

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月16日

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  • Philip Hardie,
  • Andrew Darley,
  • Rosemarie Derwin,
  • Jessica Eustace-Cook,
  • Sean Kearns,
  • Barry Mc Brien,
  • Aysha Siddiquee,
  • David Zheng,
  • Mary Mooney

摘要

Background

Generative Artificial Intelligence (Gen AI) is a type of artificial intelligence that can learn from and mimic large amounts of data to create content such as text, images, music, videos, code, and more, based on inputs or prompts. Gen AI technologies are being increasingly integrated into healthcare education, including the field of nursing, where they are utilised to support a range of pedagogical activities.

Purpose

This scoping review examined and described the application of Gen AI as a teaching, learning and assessment strategy in Nursing education and examined the ethical implications of and attitudes towards its implementation.

Methods

We conducted a scoping review using a combination of methodological approaches, including Arksey and O’Malley’s 5-step framework, the PRISMA-ScR guidelines, and JBI evidence synthesis methods and searched five databases: EMBASE (Elsevier), Web of Science Core (Clarivate), CINAHL & Medline (EBSCO), Applied Social Science Index and Abstracts, and ERIC (ProQuest). A wide search of grey literature was also conducted. Literature published in English between January 1st 2014, and July 1st 2025 was included in the review.

Results

Of the 1,251 articles retrieved, we identified 103 articles for inclusion in the review. There were 44 discussion/opinion/conference papers and 59 empirical research papers. Gen AI has predominantly been used for content creation simulation, personalised learning, tutoring, skill development and assessment. Students and Educators describe mixed attitudes towards the implementation of Gen AI, with several ethical concerns regarding the application of Gen AI in nursing education evident, including privacy, transparency, bias, and accountability issues.

Conclusion

While there is growing openness to Gen AI, a body of work remains regarding ethical and educational challenges. Recommendations for educational practice and curriculum development include a need for clear policies and guidelines to ensure the ethical use of Gen AI resources by educators and students. Further research is needed to understand long-term effects and promote responsible implementation within the context of nursing education.